6  Summary and conclusions

This section first summarises the results of the paper. It then provides some discussion around the results, restating the limitations of the analysis.

6.1  Summary of results

This paper summarises the results of a cost of illness type study aimed at estimating some of the costs associated with ill health in New Zealand using evidence from the Survey of Family, Income and Employment (SoFIE). The focus is to try to obtain first estimates of costs that might be lost in a one-year period as a result of ill health. It is acknowledged from the outset that it is not possible using SoFIE to estimate all costs associated with ill health. As such this study aims to estimate the magnitude of just some of the associated costs (the costs considered are shown in Figure 2).

Table 26 provides a summary of the estimated magnitude of the different components of ill health that can be estimated using the SoFIE data. In monetary terms the total cost of the considered components is estimated to be $5.417 billion to $12,853 billion; between 3.6% and 8.5% of GDP for a similar period.

It is not known which people may participate in the absence of ill health and therefore it is not possible to know whether this group are also those with hospital inpatient costs. To determine the total number of people affected, it is assumed that all of the 42,300 people who may additionally participate in the labour force also experience hospital costs. Under this assumption, 1,301,700 are estimated to be affected by hospital inpatient costs or indirect costs; 44.8% of all those aged over 17 years.[54][55] Owing to the assumption made, this is likely to represent a lower bound of the number of people affected.

Source: SoFIE/NZHIS Wave 3 Version 4, adjusted longitudinal weights, Statistics New Zealand

Notes:
1. Direct costs are for those aged 17 and over. Indirect costs are for working age non-students.
2. The total number of people affected is not the sum of the individual groups as the groups are not mutually exclusive; that is, some people can appear in both groups.
3. To estimate the total number of people affected it is assumed that the additional number of people who would participate in the absence of ill health are those with hospital appointments.
4. Count is from Method 1 – Maximum.

The main focus of this work is in estimating indirect costs. Around 1,196,200 working age non-students are estimated to suffer from one or more of the components of indirect costs estimated.[56] That is 61.8% of all working age non-students. The range of hours lost as a result of indirect costs is estimated to be 206.9 million to 579.6 million; 5.5% to 15.4% of total hours worked. Evaluated at the average full-time rate these hours equate to $4.127 billion to $11.563 billion; 2.7% to 7.6% of GDP.

The large range in the estimate of hours lost is a result of the large range of the estimate for presenteeism and comes from using a range of methods about the proportion of hours affected by presenteeism and a number of assumptions about the level of reduced productivity. This illustrates what a difficult concept presenteeism is to estimate, and how sensitive the estimates are to the assumptions made. In terms of hours lost the estimate for presenteeism ranges from 39.3 million to 409.0 million hours; 1.0% to 10.9% of hours worked.

In monetary terms, the estimate for presenteeism ranges from $0.724 billion to $8.160 billion; 0.5% to 5.4% of GDP. Figure 7 shows the large impact the different presenteeism estimates have on the distribution of costs over the indirect components. The outer ring and figures show the distribution of indirect costs over the different components when the maximum estimate of presenteeism is used. The inner ring and figures show the distribution when the minimum estimate of presenteeism is used. The estimate of presenteeism ranges from 18% to 71% of total indirect costs.

Irrespective of the method and assumptions used to estimate presenteeism, the estimates of absenteeism are below those for presenteeism. It is estimated that 10.3 million hours were lost owing to absenteeism; 0.3% of all hours worked. In monetary terms these hours equate to $0.205 billion; 0.1% of GDP. This is only 2.5% to 28.3% of presenteeism. Figure 7 indicates that absenteeism accounts for only 2% to 5% of indirect costs. The methods used to estimate absenteeism are known to miss a large group of absenteeism. This under coverage is illustrated when the lost hours are converted into full-time equivalent days and compared with other sources of absenteeism in New Zealand. These figures therefore represent a lower bound of the cost of absenteeism. Despite this under coverage, and in line with other research, it seems likely that absenteeism will be generally smaller in size than presenteeism. Scaling up the estimate of days lost to be in line with results from the Southern Cross research suggests costs of absenteeism may be closer to $1 billion. This is below all but one of the estimates of presenteeism.

Figure 7 – Distribution of indirect costs of ill health from SoFIE using minimum and maximum estimate of presenteeism, working age non-students, 2004/05

Source:  SoFIE/NZHIS Wave 3 Version 4, adjusted longitudinal weights, Statistics New Zealand

Working fewer hours or not working at all owing to ill health are estimated to affect different numbers of people; 458,500 and 42,300 respectively (Table 26). However, in terms of lost hours (or costs) their impact is more similar; 72.3 million hours and 88 million hours respectively (or $1.442 billion and $1.755 billion respectively). Owing to the basic models used to derive these estimates, these figures are likely to represent the upper bounds for these components. In terms of where these costs sit within the overall indirect costs, the proportion represented is heavily reliant on the estimate of presenteeism; together the cost of working less or not working accounts for between 27% and 77% of all indirect costs (Figure 7).

Taking the estimate of presenteeism derived from Method 1 and Assumption 2 (this is closest to the mid-point of the range) the hours lost owing to indirect components are estimated to be 375.1 million; 10.0% of total hours. Indirect costs are estimated to total $7.483 billion; 4.9% of GDP. The distribution of these costs over the different indirect components can be found in Figure 8.

Figure 8 – Distribution of indirect costs of ill health from SoFIE using the estimate of presenteeism closest to the mid-point (Method 1 & Assumption 2), working age non-students, 2004/05

Source:  SoFIE/NZHIS Wave 3 Version 4, adjusted longitudinal weights, Statistics New Zealand

The only direct costs included here are direct inpatient hospital costs, as these are the only costs that can be attributed to each respondent in SoFIE and related to labour force status. As such it is clear that the direct costs considered are only a small portion of wider health care costs. With that in mind, around 267,700 people (aged 17 and over) are estimated to have an ill health-related hospital appointment in the period. The cost of these hospital inpatient appointments is estimated to be $1.290 billion; 0.9% of GDP. This is below the majority of the estimated costs of presenteeism and those from working less and not working at all owing to ill health. It should be remembered that this is only one small component of direct costs.

The results presented are point estimates. As these estimates are based on survey data they are subject to sampling error. Sampling error occurs because data is only observed for a sample of the population rather than the whole of the population. Often when survey data is used, 95% confidence intervals are placed around point estimates to give an idea of the accuracy of the results. These confidence intervals reflect the upper and lower bounds between which you can be 95% sure that the true value for the population lies. Appendix H provides some indication of the sampling error associated with these estimates. The sampling variability of the estimates should be borne in mind when results from this analysis are used. While the estimate for presenteeism is a range, this range is a result of the different methods and assumptions used. It does not reflect differences owing to sampling error; in other words, it is not a confidence interval.

As well as the areas of future work that could be undertaken in this area mentioned throughout the report, there is also scope for further work looking at how costs vary for different groups (for example, by gender and by age group).